periodic_gauss_deriv

The function computes the derivative of a correlation matrix parameterized by the periodic Gaussian correlation function, with regard to the inverse range parameter.

internal

Robust parameter estimation and prediction of Gaussian stochastic
process emulators. It allows for robust parameter estimation and prediction using
Gaussian stochastic process emulator. It also implements the parallel partial
Gaussian stochastic process emulator for computer model with massive outputs
See the reference: Mengyang Gu and Jim Berger, 2016, Annals of Applied Statistics;
Mengyang Gu, Xiaojing Wang and Jim Berger, 2018, Annals of Statistics.

Mengyang Gu

RobustGaSP

Robust Gaussian Stochastic Process Emulation

Jesus Palomo

James Berger

periodic_gauss_deriv function

<dl> <dt>R0_i</dt>
<dd>
an absolute difference matrix of the i-th input vector.</dd> <dt>R</dt>
<dd>
the correlation matrix.</dd> <dt>beta_i</dt>
<dd></dd></dl>
the inverse range parameter.

Arguments

tools:::Rd_package_author("RobustGaSP")
Maintainer: tools:::Rd_package_maintainer("RobustGaSP")

Author


The derivative of periodic Gaussian correlation function with regard to the inverse range parameter — periodic_gauss_deriv

<dl>

 <dt>R0_i</dt>
<dd>
an absolute difference matrix of the i-th input vector.</dd>

 <dt>R</dt>
<dd>
the correlation matrix.</dd>

 <dt>beta_i</dt>
<dd></dd>

</dl>
the inverse range parameter.

periodic_gauss_deriv: The derivative of periodic Gaussian correlation function with regard to the inverse range parameter

Description

Usage

Value

Arguments

Author

See Also